A method for dynamically dividing tunnel rock burst grades in a construction stage

Abstract

The present disclosure provides a construction stage tunnel rock burst grade dynamic division method, which relates to the technical field of tunnel construction. First, a rock burst grade dynamic fine division index system is established, and different geological units are divided according to the actual situation on site. Then, rock burst events and rock burst event index sample data are collected. Through the data collected by multiple indexes, compared with the traditional single index judgment method, the evaluation can be more accurate. Finally, the variable weight function suitable for rock burst events and the unascertained attribute measure function of each index of rock burst grade division are proposed. Based on the combined weight of each index of the first rock burst event in the same geological unit, the dynamic weight of each index of the remaining rock burst events in the same geological unit is calculated, and the dynamic evaluation of the rock burst event grade in the same geological unit is realized. The beneficial effect is that the rock burst grade in the construction stage can be divided more systematically and comprehensively.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of tunnel construction, in particular to a method for dynamically dividing tunnel rock burst grades in a construction phase. BACKGROUND

[0002] Rock burst refers to a phenomenon of sudden and violent failure in a free-standing rock mass in a deep or high tectonic stress area of underground mining. This phenomenon is also known as rock burst. The cause is that the strain energy accumulated in the free-standing rock mass is suddenly and violently released, causing the rock mass to break like an explosion. The impact ground pressure causes a large amount of rock to collapse, and produces a loud noise and air wave impact.

[0003] Rock burst is a common dynamic failure phenomenon in the construction process of deep underground engineering. When the high elastic strain energy accumulated in the rock mass is greater than the energy consumed by rock failure, the balance of the rock mass structure is broken, and the excess energy causes the rock to burst, causing the rock fragments to peel off and collapse from the rock mass.

[0004] With the advancement of deep underground engineering, such as deep buried tunnels, underground workshops and mine roadways, rock burst disasters pose a serious threat to people's life and property safety. Different intervals of the same tunnel can have different grades of rock burst events. At present, most of the rock burst grade division index systems are divided according to the depth of the explosion pit and the rock strength stress ratio, but do not consider the development of structural planes and the dynamic effect of construction. At the same time, the division according to the depth of the explosion pit and the rock strength stress ratio is too rough, and the research on multi-index dynamic fine division of rock burst grade is insufficient. Therefore, as the project progresses, the rock burst grade division cannot accurately reflect the true situation of the rock burst grade, which may lead to inaccurate judgments and cannot provide reference standards for subsequent construction, seriously threatening the construction and safety of deep buried tunnel projects. Therefore, by considering the newly emerging multi-index and taking the same tunnel as the basis, multi-index dynamic fine division of rock burst grade can provide valuable rock burst information. SUMMARY

[0005] One of the technical problems to be solved by the present disclosure is that the existing division of rock burst grade according to the depth of the explosion pit and the rock strength stress ratio is too rough, and the research on multi-index dynamic fine division of rock burst grade is insufficient.

[0006] To solve the above technical problems, the present disclosure provides a method for dynamically dividing rock burst grades in a tunnel construction phase, which comprises:

[0007] S1: establishing a dynamic fine division index system for rock burst grade;

[0008] The index system comprises: blast crater damage depth, blast crater damage length, blast rock block thickness, blast rock block morphology, blast rock block movement characteristics, sound characteristics, rock mass structure surface integrity, rock mass fracture duration, support damage degree, structure surface occurrence and free surface characteristics, structure surface group number and spacing, and rock strength stress ratio.

[0009] S2: different geological units are divided according to geological prediction, on-site drilling and excavation, and rock burst events are collected;

[0010] S3: according to the data of each index of the rock burst event in S2, the objective data weight and the subjective experience weight of each index are calculated,

[0011] The objective data weight is obtained by the CRITIC method weight and the entropy value method weight, and the subjective experience weight is obtained by the AHP method weight and the DEMATEL weight.

[0012] S4: according to the objective data weight and the subjective experience weight in S3, the combined weight is calculated by using the game theory method;

[0013] S5: the relative evaluation of the first rock burst event grade of the same geological unit is carried out by using the TOPSIS method and combining the combined weight in S4;

[0014] S6: according to the variable weight theory and the unascertained attribute measure theory, the variable weight function of the rock burst event and the unascertained attribute measure function of each index in the rock burst event are obtained;

[0015] S7: based on the combined weight of each index of the first rock burst event in the same geological unit, the dynamic weight of each index of the remaining rock burst events under the same geological unit is calculated, and the dynamic evaluation of the rock burst event grade in the same geological unit is realized.

[0016] In some embodiments, the foregoing construction stage tunnel rock burst grade dynamic division method, wherein the variable weight function and the unascertained attribute measure function in S6 are:

[0017] S61, the state variable weight function S(x) and the index variable weight function W(x) are established by using the variable weight theory

[0018]

[0019] Wherein, x needs to be processed in the index direction, the positive index is processed in the positive direction, and the negative index is processed in the reverse direction, W 0 is the index constant weight; c=0.2, b=0.25,

[0020]

[0021] Among them, x 轻 The index value representing the upper limit of minor rock burst, x 中 The index value representing the upper limit of moderate rock burst, x 强 The index value representing the upper limit of strong rock burst, x 事件 The index value representing a rockburst event within the same geological unit;

[0022] S62. Using the unascertained attribute measurement theory, establish the unascertained attribute measurement function of each index of rock burst event;

[0023] Among them, the unascertained attribute measurement function of the blast crater damage depth is:

[0024]

[0025] The unascertained attribute measurement function of the blast crater damage length is:

[0026]

[0027]

[0028] The unascertained attribute measurement function of the thickness of the blasted rock mass is:

[0029] The unascertained attribute measurement function of the motion characteristics of the blasting rock mass is:

[0030] The unascertained attribute measurement function of the support failure degree is:

[0031]

[0032]

[0033] The unascertained property measurement function of rock strength stress ratio is:

[0034]

[0035] In some embodiments, in the aforementioned method for dynamically classifying rockburst levels in a tunnel during construction, the qualitative indicators in the index system include: morphology of blasted rock blocks, acoustic characteristics, integrity of rock mass structural surfaces, duration of rock mass rupture, occurrence of structural surfaces, and characteristics of free-facing surfaces; and the quantitative indicators include: depth of blasting crater damage, length of blasting crater damage, thickness of blasted rock blocks, movement characteristics of blasted rock blocks, degree of support damage, number and spacing of structural surface groups, and rock strength-stress ratio.

[0036] Wherein, the quantitative indicators adopt real data, and except the number of structural plane sets and the interval, the rest indicators need to construct unascertained attribute measure function; the qualitative indicators are determined by mathematical fuzzy method, and the qualitative indicators and the number of structural plane sets and the interval do not need to construct single indicator unascertained attribute measure function, and the unascertained attribute measure is represented by 0 or 1, so as to obtain single indicator evaluation matrix.

[0037] In some embodiments, the foregoing construction stage tunnel rock burst grade dynamic division method, wherein the quantitative indicators take the upper limit value of different rock burst grades; wherein the rock burst grades include: slight rock burst, medium rock burst and intense rock burst.

[0038] In some embodiments, the foregoing construction stage tunnel rock burst grade dynamic division method, wherein the calculation method of S7 comprises:

[0039] S71: using game theory algorithm, calculating the index combination weight of the first rock burst event in the same geological unit;

[0040] S72: according to the index variable weight function W(x), calculating the dynamic weight of each index of the rest rock burst events in the same geological unit;

[0041] S73: according to the established rock burst grade, calculating the unascertained attribute measure of each index of rock burst grade division, and according to the weighted sum of dynamic weight and unascertained attribute measure, the comprehensive attribute measure μ can be obtained ik , according to the confidence degree criterion, the attribute recognition is carried out, and the dynamic evaluation of rock burst event grade in the same geological unit is realized.

[0042] In some embodiments, the foregoing construction stage tunnel rock burst grade dynamic division method, wherein the entropy value method weight and AHP method weight in S3 are used to reflect the contribution degree of each index in the system, and the CRITIC method weight and DEMATEL weight are used to reflect the mutual influence between each index.

[0043] In some embodiments, the foregoing construction stage tunnel rock burst grade dynamic division method, wherein the subjective experience weight in S3 is obtained by the product normalization of AHP method weight and DEMATEL method weight.

[0044] Through the technical solution, the construction stage tunnel rock burst grade dynamic division method provided by the present disclosure establishes a rock burst grade dynamic fine division index system, divides different geological units according to the actual situation on site, collects rock burst event and rock burst event index sample data. Compared with the traditional single index judgment method, the data collected by multiple indexes can be more accurate in evaluation, and the subjective weight and objective weight are calculated based on this, and the combination weight of each index is calculated by using the game theory method. Finally, the relative evaluation of the first rock burst event grade of the same geological unit is realized by using the approximation ideal solution sorting method, and according to the variable weight theory and the unascertained attribute measurement theory, the variable weight function suitable for the rock burst event and the unascertained attribute measurement function of each index of the rock burst grade division are proposed. Based on the combination weight of each index of the first rock burst event of the same geological unit, the dynamic weight of each index of the remaining rock burst events of the same geological unit is calculated, the dynamic evaluation of the rock burst event grade in the same geological unit is realized, and the rock burst grade in the construction stage can be more systematically and comprehensively divided. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor.

[0046] Figure 1 The flowchart of the construction stage tunnel rock burst grade dynamic division method provided by the embodiment of the present disclosure is shown in the figure.

[0047] Figure 2 The construction stage tunnel rock burst grade dynamic division index system provided by the embodiment of the present disclosure is shown in the figure.

[0048] Figure 3 The TSP division graph of different geological units provided by the embodiment of the present disclosure is shown in the figure.

[0049] Figure 4 The parameter graph of different geological units provided by the embodiment of the present disclosure is shown in the figure.

[0050] Figure 5 The microcosmic geological distribution graph of a certain macroscopic geological unit provided by the embodiment of the present disclosure is shown in the figure.

[0051] Figure 6 The state variable weight function S(x) and the image provided by the embodiment of the present disclosure are shown in the figure. DETAILED DESCRIPTION

[0052] The embodiments of the present disclosure will be described in further detail below with reference to the drawings and examples. The detailed description and drawings of the following examples are used to exemplarily illustrate the principles of the present disclosure, but cannot be used to limit the scope of the present disclosure, and the present disclosure can be implemented in many different forms, not limited to the specific examples disclosed herein, but includes all technical solutions falling within the scope of the claims.

[0053] The present disclosure provides these examples in order to make the present disclosure thorough and complete, and fully convey the scope of the present disclosure to those skilled in the art. It should be noted that: unless otherwise specifically stated, the steps, numerical expressions and numerical values set forth in these examples should be interpreted as merely exemplary, not as limiting.

[0054] All terms used in the present disclosure have the same meaning as understood by those skilled in the art to which the present disclosure belongs, unless otherwise specifically defined.

[0055] Techniques, methods and devices known to those of ordinary skill in the relevant art can not be discussed in detail, but where appropriate, the techniques, methods and devices should be considered as part of the specification.

[0056] Embodiment one

[0057] S1, through investigation and reference, establish the dynamic fine division index system of rockburst grade in construction stage, reference attached Figure 2 Among them, the qualitative index is: the shape of the falling rock, the sound characteristic, the structure surface integrity of the rock mass, the rock mass fracture duration, the structure surface occurrence and the characteristics of the free surface; the quantitative index is: the damage depth of the explosion crater (m), the damage length of the explosion crater (m), the thickness of the falling rock (cm), the movement characteristics of the falling rock (m / s), the support damage degree (T / h), the structure surface group number and spacing, and the rock strength stress ratio; the quantitative index uses real sample data; the qualitative index can be determined by mathematical fuzzy method, and the value 1 represents slight rockburst, 2 represents moderate rockburst, 3 represents strong rockburst, and 4 represents extremely strong rockburst.

[0058] S2, adopt TSP seismic wave exploration to divide geological units, take H3DK2+019.8~H3DK1+909.8 rockburst section as an example, divide geological units, reference Figures 3-5, this forecast see the face reveals the surrounding rock is granulite and granodiorite, weak weathering, the overall surrounding rock is relatively complete, hard rock. Face without water, face self-stability. TSP forecast conclusion is divided into 10 geological units, including H3DK2+020-H3DK1+996, H3DK1+996-H3DK1+992, H3DK1+992-H3DK1+985, H3DK1+985-H3DK1+983, H3DK1+983-H3DK1+976, H3DK1+976-H3DK1+968, H3DK1+968-H3DK1+942, H3DK1+942-H3DK1+930, H3DK1+930-H3DK1+917, H3DK1+917-H3DK1+910.

[0059] S3, first establish the original database, as shown in Table 1, wherein the number of structural plane group and spacing, rock strength stress ratio are positive indicators, and the others are negative indicators, wherein the greater the index, the higher the rock burst grade, the subjective experience weight vector of the index system can be obtained by AHP weight and DEMATEL weight calculation W1={0.3323, 0.0768, 0.0704, 0.0199, 0.0443, 0.0060, 0.0363, 0.0038, 0.2644, 0.0272, 0.0227, 0.0959}; the objective data weight can be obtained by CRITIC weight and entropy weight method, and the upper limit critical value of rock burst grade and rock burst case index measured data are regarded as the relative evaluation scheme of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) in rock burst grade division;

[0060] Table 1 original database of first rock burst index of the same geological unit

[0061]

[0062]

[0063] Wherein, m is the number of evaluation objects; n is the number of evaluation indexes; x ij The jth index of the ith evaluation object, while the number of structural plane group and spacing, rock strength stress ratio are positive indicators, and the others are negative indicators, the greater the index, the higher the rock burst grade, and the processing of positive indicators and negative indicators is shown in the following formula:

[0064] Positive index positive processing:

[0065]

[0066] Negative index inverse processing:

[0067]

[0068] The rock burst original evaluation matrix X is normalized to obtain X * ij

[0069]

[0070] According to the entropy method, the objective data weight vector W2 of the index is calculated as {0.0673, 0.0662, 0.0970, 0.0847, 0.1571, 0.0749, 0.0749, 0.0749, 0.0670, 0.0749, 0.0749, 0.0864}, and the objective data weight vector W3 of the index is calculated as {0.0500, 0.0514, 0.1513, 0.1674, 0.1217, 0.0641, 0.0641, 0.0641, 0.0594, 0.0641, 0.0641, 0.0786} by CRITIC method, and the combination weight w* of the subjective and objective weights is calculated by game theory.

[0071]

[0072] Solving (α1, α2, …, α L ), and normalizing

[0073]

[0074] Finally, the combination weight w* is obtained:

[0075]

[0076] Thus, the combination weight w* is obtained:

[0077]

[0078] The linear equation system solution is: α1=0.9792, α2=-1.2572, α3=1.4416, and after normalization, the combination weight vector w* is obtained as {0.27, 0.06, 0.14, 0.13, 0.02, 0.00, 0.03, 0.00, 0.22, 0.02, 0.02, 0.08}.

[0079]

[0080] Finally, the combination weight vector w* is obtained as {0.27, 0.06, 0.14, 0.13, 0.02, 0.00, 0.03, 0.00, 0.22, 0.02, 0.02, 0.08}.

[0081] S4, combine the evaluation index combination weight with the TOPSIS method to establish a combination weighting-TOPSIS evaluation system. X * ij and the combination weight, to obtain the weighted normalized matrix V.

[0082]

[0083] The maximum value of each evaluation index is selected to constitute the "positive ideal solution v + = {0.27, 0.06, 0.14, 0.13, 0.02, 0, 0.03, 0, 0.22, 0.02, 0.02, 0.08} ", and the minimum value constitutes the "negative ideal solution v － = {0, …, 0} ".

[0084] The distance between the evaluation object and the positive and negative ideal solutions, i.e. the Euclidean distance, is calculated as follows:

[0085]

[0086] The Euclidean distance between the evaluation object and the positive and negative ideal solutions is calculated by the formula, D + 轻微岩爆临界 = 0, D + 中等岩爆临界 = 0.12, D + 强烈岩爆临界 = 0.39, D + 首次岩爆 = 0.21; D - 轻微岩爆临界 = 0.42, D - 中等岩爆临界 = 0.31, D - 强烈岩爆临界 = 0.05, D - 首次岩爆 = 0.31.

[0087] The closeness C i is calculated as follows,

[0088]

[0089] Therefore, C i ∈ (0, 1), C 轻微岩爆临界 = 1.0000, C 中等岩爆临界 = 0.7222, C 强烈岩爆临界 = 0.1216. The larger the relative closeness C value, the closer the evaluation case to the positive ideal solution, and the smaller the rockburst grade of the event; the smaller the C value, the closer the evaluation case to the negative ideal solution, and the larger the rockburst grade. According to the critical value of C of different rockburst grades, the rockburst grade of a rockburst event is evaluated by the interpolation method, and it is reordered, i.e. the relative evaluation of the first rockburst grade of the same geological unit is obtained, as shown in Table 2 below.

[0090] Table 2 Closeness C of the first rockburst case of the same geological unit

[0091] Case C value Rockburst ranking Rockburst grade First rockburst 0.5989 1 Strong rockburst

[0092] When dynamically evaluating the rockburst level of the same geological unit, the original database of the second rockburst of the same geological unit is established in combination with the calculation of the first rockburst event, such as Figure 1 and as shown in Table 3 below.

[0093] Table 3 Original database of the second rockburst index of the same geological unit

[0094]

[0095]

[0096]

[0097] In the formula, m is the number of evaluation objects; n is the number of evaluation indicators; x ij Represents the jth indicator of the i-th evaluation object.

[0098] The original evaluation matrix X of the second rockburst is normalized, the positive indicators are positively processed, and the negative indicators are reversed, referring to formulas (31) and (32), where the number and spacing of structural surface groups and rock strength stress ratio are positive indicators, and the others are negative indicators, that is, the larger the indicator, the higher the rockburst grade, and X is obtained. * ij

[0099]

[0100] Finally, from formula (3-5), we can get

[0101] μ={1,...,1}; λ={0.80,0.81,0.57,0.50,0.56,0.50,0.50,0.50,0.75,0.50,0.50,0.33};

[0102] α={0,……,0};Let c={0.2,……,0.2};b={0.25,……,0.25},then a={0.65,0.68,0.38,0.35,0.38,0.35,0.35,0.35,0.35,0.55,0.35,0.35,0.3},all satisfy

[0103] The combined weights of the first rockburst event indicators of the same geological unit are known, w* = {0.27, 0.06, 0.14, 0.13, 0.02, 0.00, 0.03, 0.00, 0.22, 0.02, 0.02, 0.08}, and the formula (1) and the appendix show that Figure 6The state variable weight function value of each indicator of the second rock burst can be obtained as S(xsecond rock burst) = {0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.25, 0.2, 0.2, 0.25, 0.2}; the dynamic weight of each indicator of the second rock burst can be obtained as W(xsecond rock burst) = {0.27, 0.06, 0.14, 0.13, 0.02, 0, 0.03, 0, 0.22, 0.02, 0.02, 0.08} by formula (2);

[0104] According to the rockburst index unascertained attribute measurement function (Equations 6 to 29), the unascertained attribute measurement value μ of each index is calculated respectively. ijk and comprehensive attribute measure μ ik (Formula 39) and fill in the following Table 4,

[0105]

[0106] Where: w j is the dynamic weight of each indicator of the second rockburst.

[0107] Attribute identification is performed according to the confidence criterion. The confidence λ is generally set to 0.6-0.7. The confidence λ value is 0.65 in this paper, referring to the relevant literature. If the evaluation space {D1, D2, …, D4} is ordered and D1>D2> …>D4, then D1 is a mild rock burst, D2 is a moderate rock burst, D3 is a strong rock burst, and D4 is an extremely strong rock burst.

[0108] Where k is an integer, then the rock burst event is considered to belong to the kth evaluation category D k .

[0109] Table 4. Second rockburst index attribute measurement table

[0110]

[0111]

[0112] The attribute identification result is determined by the above formula (40). 0.71>0.65, so the comprehensive attribute measurement of the rock burst event is D1, that is, a minor rock burst. If the comprehensive attribute measurement μ ik Zhong Ruo μ i1 If μ is greater than 0.65, it is D1 level; i1 is less than 0.65, and μ i1 and μ i2 If the sum of μ is greater than 0.65, it is D2, that is, medium rock burst; i1 and μ i2 The sum is less than 0.65, and μ i1 、μ i2 and μi3 If the sum of μ i1 , μ i2 and μ i3 is less than 0.65, and μ i1 , μ i2 , μ i3 and μ i4 is greater than 0.65, it is D4, i.e. extremely strong rock burst.

[0113] Thus far, the embodiments of the present disclosure have been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein according to the above description.

[0114] Although some specific embodiments of the present disclosure have been described in detail through examples, those skilled in the art should understand that the above examples are only for illustration, and are not intended to limit the scope of the present disclosure. Those skilled in the art should understand that the above embodiments can be modified or some technical features can be replaced equivalently without departing from the scope and spirit of the present disclosure. In particular, as long as there is no structural conflict, the technical features mentioned in each embodiment can be combined in any way.

Claims

1. A method for dynamically classifying tunnel rockburst levels during construction, characterized in that: include: S1: Establish a dynamic and fine classification index system for rockburst levels; The index system includes: blasting crater damage depth, blasting crater damage length, blasting rock thickness, blasting rock shape, blasting rock movement characteristics, sound characteristics, rock mass structural surface integrity, rock mass rupture duration, support damage degree, structural surface occurrence and free surface characteristics, structural surface group number and spacing, rock strength stress ratio; S2: Divide different geological units based on geological forecasts, on-site drilling and excavation conditions, and collect rockburst events; S3: Based on the data of each indicator of rock burst events in S2, calculate the objective data weight and subjective experience weight of each indicator. Among them, the objective data weight can be obtained through the CRITIC method weight and the entropy method weight, and the subjective experience weight can be obtained through the AHP method weight and the DEMATEL weight; S4: Based on the objective data weights and subjective experience weights in S3, the combination weights are calculated using game theory methods; S5: The level of the first rockburst event in the same geological unit is relatively evaluated by using the approximate ideal solution ranking method and combining the combined weights in S4; S6: Based on the variable weight theory and the unascertained attribute measurement theory, the variable weight function of the rock burst event and the unascertained attribute measurement function of each indicator in the rock burst event are obtained; S7: Calculate the dynamic weights of the remaining rockburst event indicators in the same geological unit based on the combined weights in S4 and the variable weight function in S6; S8: Based on the unascertained attribute measurement function of each indicator in S6, the unascertained attribute measurement of each indicator is calculated. The product value of the dynamic weight of each indicator and the unascertained attribute measurement can be added to obtain the comprehensive attribute measurement. Attribute identification is performed according to the confidence criterion to realize the dynamic evaluation of the rockburst event level within the same geological unit.

2. A method for dynamically classifying rockburst levels in tunnels during construction according to claim 1, characterized in that: The variable weight function and unascertained attribute measurement function in S6 are specifically: S61. Using variable weight theory, establish the state variable weight function S(x) and the index variable weight function W(x) Among them, x needs to be processed in the indicator direction, positive indicators are processed positively, and negative indicators are processed reversely. j 0 is the constant weight of the indicator, c=0.2,b=0.25, satisfy Among them, x 轻 The index value representing the upper limit of minor rock burst, x 中 The index value representing the upper limit of moderate rock burst, x 强 The index value representing the upper limit of strong rock burst, x 事件 The index value representing a rockburst event within the same geological unit; S62. Using the unascertained attribute measurement theory, establish the unascertained attribute measurement function of each index of rock burst event; Among them, the unascertained attribute measurement function of the blast crater damage depth is: The unascertained attribute measurement function of the blast crater damage length is: The unascertained attribute measurement function of the thickness of the blasted rock mass is: The unascertained attribute measurement function of the motion characteristics of the blasting rock mass is: The unascertained attribute measurement function of the support failure degree is: The unascertained property measurement function of rock strength stress ratio is: Among them, x ij Represents the jth indicator of the i-th evaluation object.

3. The method for dynamically classifying rockburst levels in a tunnel during construction according to claim 1, wherein: The qualitative indicators in the index system are: the shape of the blasted rock blocks, the sound characteristics, the integrity of the rock structure surface, the duration of rock mass rupture, the occurrence of the structure surface and the characteristics of the free surface; the quantitative indicators are: the depth of the blasting crater, the length of the blasting crater, the thickness of the blasted rock blocks, the movement characteristics of the blasted rock blocks, the degree of support damage, the number and spacing of the structure surface groups, and the rock strength stress ratio; Among them, quantitative indicators use real data, and except for the number and spacing of structural surface groups, the other indicators need to construct unascertained attribute measurement functions; qualitative indicators are determined by mathematical fuzzy method. At the same time, qualitative indicators and the number and spacing of structural surface groups do not need to construct single-indicator unascertained attribute measurement functions. The unascertained attribute measurement is represented by 0 or 1 to calculate the single-indicator evaluation matrix.

4. A method for dynamically classifying rockburst levels in a tunnel during construction according to claim 3, characterized in that: The quantitative indicators are upper limits of different rock burst levels; Among them, rock burst levels include: minor rock burst, moderate rock burst and severe rock burst.

5. The method for dynamically classifying rockburst levels in a tunnel during construction according to claim 1, wherein: The entropy method weights and AHP method weights in S3 are used to reflect the contribution of each indicator in the system, and the CRITIC method weights and DEMATEL method weights are used to reflect the mutual influence between each indicator.

6. The method for dynamically classifying rockburst levels in a tunnel during construction according to claim 1, characterized in that: The subjective experience weight in S3 is obtained by multiplying the AHP weight and the DEMATEL weight.

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